This research presents an application of artificial neural networks in demand forecasting by using MATLAB Software. Keeping in mind that in any planning process forecasts play a fundamental role, being one of the bases for; planning, organizing and controlling production. It gives priority to the most critical nodes and their key activities, so that, the decisions made about them will generate the greatest possible positive impact. The methodology applied demonstrates the quality of the solutions found which are compared with traditional statistical methods to demonstrate the value of the solution proposed. When the results show that the minimum quadratic error is reached with the application of artificial neural networks, a better performance is obtained. Therefore, a suitable horizon is established for the planification and decision making in the metal-mechanical industry for the use of artificial intelligence in the production processes.

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This paper provides a current and future business analysis of small food services and products company. Analysis methods include tabulation of the dataset, as well as hypothesis testing by comparison between directly proportional variables such as price/quality and recommendations/customer loyalty. Other calculations include key economic dimensions, decisions influenced by the JobKeeper payment scheme, data on capital expenditure expectations, and future business conditions. The results of the analyzed data show that customer and company behavior is in parallel with global trade. In particular, the growth of the digital market and customer loyalty where they find a product that meets their quality needs. The analysis finds that the company's prospects in its current position are positive. Of the four variables identified, two will be reinforced by the economic and market strategies to be implemented. The work also investigates the fact that the analysis carried out has possible limitations. Some of the limitations are that not all the company was able to register in the JobKeeper payment scheme and the lack of use of key tools for sustainable marketing.